This invention relates to improved methods and apparatus for forming multi-dimensional images from compressed sampled data, such as radar images in synthetic aperture radar systems.
Synthetic aperture radar (SAR) is a well-known technique for improving resolution in radar ground mapping. This is typically done by flying an airplane over the ground to be mapped, and successively transmitting a sequence of radar pulses. With the forward motion of the airplane, each successive radar pulse is transmitted from a position a little farther along on the flight path, thus simulating a very long radar array.
Return signals from the transmitted pulses are sampled in the airplane and either recorded aboard the airplane and brought back to a ground station for processing, or directly transmitted to the ground station for processing--to thereby develop the desired image. The processing carried out is complex, employing such techniques as fast fourier transform (FFT), inverse FFT or correlation. These operations require many floating-point multiplications, floating-point additions, floating-point subtractions and floating-point divisions, which can be carried out only by sophisticated processors.
In a co-pending application, Ser. No. 157,199, filed Feb. 17, 1988, a so-called "method of forming visual images in radar by utilizing preconvolved quantized vectors" is described in which sampled radar returns are represented as vectors. For example, samples of the return signal from one pulse are arranged in one row of an array, samples of the return signal from the next pulse are arranged in the next row of the array, etc. Groups of adjacent samples (source vectors) are compared to a set (codebook) of allowable vector patterns (codevectors) which have been previously determined to be statistically representative and stored. The codevectors all have assigned indices identifying them, and the index of the closest codevector to each source vector is either stored or transmitted to a receiver which also has a copy of the codebook. Such comparisons thus yield a small array of indices which identifies a larger array of source vectors. This process of "data compression" of the array of source vectors into a smaller array of indices is called vector quantization (VQ).
The array of indices is then used to identify and read from locations of a memory so-called preprocessed vectors which have indices corresponding to those in the array. These preprocessed vectors are convolved counterparts of codevectors identified by the indices. The identified preprocessed vectors are then added together in a predetermined fashion, while maintaining a certain offset between them, to obtain a result which determines the visual image of the radar returns (ground map). This preprocessing involves "focusing" the radar returns first in the range direction (called range compression) and then finally in the azimuth direction (called azimuth compression).
With the above-described process, computational and processing power is exchanged for larger memories to store the codebooks and preprocessed vectors. Savings are thus realized in computational hardware and time.
With the above method, the steps of range and azimuth focusing are performed in a single step to produce the preprocessed vectors. Since the azimuth focussing is a function of (dependent on) the range, low resolution images are obtained with the method. To obtain higher resolution images, the processing steps could be repeated for each of various ranges, but such an approach would eliminate the advantage realized by the method of reducing computational hardware and time.
It has been discovered with the present invention that even further significant savings can be realized in both computational hardware and memory requirements for SAR and like processing. This is accomplished by performing the steps of range focussing and azimuth focussing separately, i.e., storing two sets of preprocessed vectors, one for range focussing and one for azimuth focussing, and twice convolving and storing one-dimensional arrays (or a series of one-dimensional arrays) rather than a two-dimensional array.